The present application relates to methods and systems for identifying geographic areas of potential interest from a plurality of geographic areas.
Systems exist for identifying geographic areas that are potentially of interest to people, e.g., who are in the general geographic area or who are planning to visit the general geographic area. Some of these systems use web crawlers to identify points of potential interest, such as restaurants, hotels, etc., from written reviews and/or numerical ratings submitted to websites, such as Yelp, Yellowbot.com, by persons that have visited a particular geographic area. This method of identifying points of interest, however, has significant drawbacks. For instance, written reviews without corresponding numerical ratings are difficult for the system to quantify resulting in unreliable identifications. Even when a numerical rating is available, these systems derive the rating from an image tag in the webpage containing therein the numerical rating, such as the image tag [img class=“stars—3_half rating average” width=“83”], without regard to the time that has passed since the reviewer submitted the numerical rating thereby ignoring any variances in the quality of service at the point of interest over time resulting again in unreliable identifications. Some other systems utilize Google Search APIs and Yahoo! Local Search APIs. But similar issues are encountered. Further, reviews are often old even for relatively popular geographic areas.
Accordingly, there is a need for methods and systems for identifying points of interest that are more reliable and/or that do not exhibit one or more of the disadvantages noted above.